Upload app.py

app.py

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+import cv2
+import numpy as np
+import gradio as gr
+
+def show_preds_video():
+            
+
+    background = cv2.imread("background2.png")
+    background = cv2.cvtColor(background,cv2.COLOR_BGR2GRAY)
+    background = cv2.GaussianBlur(background,(21,21),0)
+
+    
+    # def detect_motion(thres_input):
+    cap = cv2.VideoCapture('CCTV.avi')
+
+    # Initialize video writer for processed video
+    fourcc = cv2.VideoWriter_fourcc(*'mp4v')
+    out = cv2.VideoWriter("processed_video.mp4", fourcc, cap.get(cv2.CAP_PROP_FPS), (int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)), int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT))))
+
+    while True:
+        # Capture current frame
+        ret, frame = cap.read()
+
+        # If end of video, break loop
+        if not ret:
+            break
+
+        # Convert current frame to grayscale
+        gray = cv2.cvtColor(frame, cv2.COLOR_BGR2GRAY)
+        gray = cv2.GaussianBlur(gray,(21,21), 0)
+
+
+        # reaize background to match current frame
+        background = cv2.resize(background, (gray.shape[1], gray.shape[0]))
+
+        # Calculate absolute difference between current frame and background
+        diff = cv2.absdiff(background,gray)
+        thresh = cv2.threshold(diff,30,255,cv2.THRESH_BINARY)[1]
+        thresh = cv2.dilate(thresh, None, iterations = 2)
+
+        cnts,res = cv2.findContours(thresh.copy(),cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
+
+        for contour in cnts:
+            if cv2.contourArea(contour) < 10000 :
+                continue
+            (x,y,w,h) = cv2.boundingRect(contour)
+            cv2.rectangle(frame,(x,y),(x+w,y+h),(0,255,0), 3)
+
+        # # Check if any contours were found
+        if len(contour) > 0:
+            # Motion detected, trigger alarm
+            message = "Motion detected !!!"
+            
+        else:
+            # No motion detected
+            message = "No motion detected"
+
+        # Display current frame and processed frames
+        cv2.putText(frame, message, (10, 100), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 2)
+
+        # Write processed frame to output video
+        out.write(frame)
+
+  
+    return "processed_video.mp4"
+
+outputs_video = [
+gr.outputs.Video(label="Processed Video"),
+]
+
+inputs_video = [  #gr.components.Video(type="filepath", label="Input Video", visible =False), 
+               ]
+
+interface_video = gr.Interface(
+    fn=show_preds_video,
+    inputs=inputs_video,
+    outputs=outputs_video,
+    title="Security - Trespasser monitoring  ",
+    cache_examples=False,
+    allow_flagging=False,
+    capture_session=True,
+    cache=True
+
+).queue().launch()
+